Aladdin Mhemed

I developed a medical education platform that incorporated AI to evaluate medical students' responses and provide relevant quizzes. The platform aimed to replicate real-life patient interactions, providing students with a dynamic and immersive learning experience. Upon evaluation of their conversations, students received a score.

To build the platform, I leveraged my expertise in React and its ecosystem to create quiz wizards, chatbots, and data visualization artifacts. Working closely with the design team, I transformed their Figma wireframes into fully responsive and pixel-perfect React pages, and the main CSS framework was MUI.

To facilitate real-time communication between students and the platform, I utilized Socket.IO. For data visualization, I incorporated Charts.js and SVG. We employed Jira for project management to maintain an Agile workflow and held daily scrum meetings. Lastly, I established a CI/CD pipeline using GitHub and CircleCI.

A graph builder lets users intuitively construct and navigate organizational structures through a graphical interface. It offers features for creating, adjusting, and visually representing nodes and their interconnections, capturing organizational environments' intricate hierarchies and dynamics. A graph builder stands out for its real-time update functionality, advanced data-driven insights, and proactive alert detection mechanisms, making it an essential organizational analysis and management tool.

My responsibilities:
• Developed a Node.js/Express back end to support RESTful API integration, consuming external HRMS, CRM, and ERP systems data.
• Implemented real-time data normalization.
• Utilized Neo4j graph database and Cypher for generic data modeling.
• Deployed the MVP using AWS Elastic Beanstalk for efficient scaling and management.
• Implemented a responsive interface using Angular 4, integrating D3.js for data-driven graphical representations and Fabric.js for enhanced canvas manipulation, enhanced with RxJS for reactive programming patterns.

I created many D3.js, HTML5 Canvas, and SVG custom charts for various enterprise applications and the apps were made in React, so I integrated my work into new pages in their existing apps. Few charts consumed real-time data.

I designed and developed a dashboard for MTN Guinea telecommunication company to monitor calls that posed security threats. This involved implementing both the back-end and front-end components of the application. To query the extensive data database, which added one billion rows of data each day,

I utilized PrestoDB queries in the back end to write SQL queries. In addition to this, I created a REST API in the back end, which was consumed by the front-end.

For the front end, I used Angular 8 and implemented pixel-perfect, responsive pages from Figma wireframes. I continued to refine the design and functionality of the application through multiple development cycles until it was ready for deployment. Finally, I delivered the completed application to MTN Guinea telecommunications company.

As part of my work, I developed a set of real-time KPI dashboards for MTN Telecommunications that catered to different levels of management. These KPIs were extracted from large volumes of telecommunication data, including voice, SMS, internet consumption, and incoming and outgoing calls.

To achieve this, I leveraged three primary tools:

• Flare from Ligadata – I used this tool to automate data cleaning, normalization, and logging. It helped to ensure that the data was accurate and ready for analysis.
• Kamanga from Ligadata – This tool provided APIs that I used to apply machine learning and AI to detect anomalies, threats, alerts, and failures in real-time, allowing management to take quick action.
• Apache Kafka – To wrap all the code that queried APIs from Flare and Kamanga. This helped to streamline the data flow and update KPIs in real time.

I also created a user-friendly, secure, and authenticated front end. I used Socket.io, Angular, and Power BI to create fully responsive and visually rich data visualizations. These dashboards provided an intuitive and interactive interface for management to view key metrics, make data-driven decisions, and monitor real-time performance.

As a highly talented full-stack developer (and member of a fantastic team at Ebdaa), I was (and am now partly) working on a task board inspired by Kanbanize.com, leveraging cutting-edge technology and implementing practically all functionalities while paying special attention to data visualization.

The project includes all the charts and graphics necessary to provide users with a clear and comprehensive visualization of their data. Data visualization includes bar charts, pie charts, line charts, area charts, scatterplots, and heat maps, as well as Kanban boards with swimlane diagrams and Gantt charts. Also, icons, progress bars, and badges provide additional context and information about tasks.

AWS-selected products allow the application to scale effortlessly, and Amazon RDS, MongoDB Atlas, and Redis Cache offer smooth data storage and retrieval.

We decided to use both REST APIs and GraphQL allowing for more flexibility. Also, TDD, and CI/CD are used to ensure each feature is tested and functioning correctly before deployment. Moreover, I utilized D3.js, HTML5 Canvas, SVG, Chart.js, and Fabric.js to create all the necessary visualizations.

(Please refer to my experience at Ebdaa company)

In my previous engagement with Spectrum Environmental Solutions as a member of the development team, I contributed to creating an enterprise application to promote air-monitoring instruments. The application offered customized versions of the web app tailored to customers' specific requirements, including their chosen methodology, purchased equipment, and other geographical and logistical factors.

The web apps were designed to be data-driven. They collect complex data from the monitoring instruments and present them in real time in an intuitive and visually appealing front-end interface, complete with state-of-the-art data visualization tools.

Working on a Toptal engagement for Sei Healthcare, I created an MVP for an innovative medical education software to offer immersive patient case simulations. This powerful app provides medical professionals and students with virtual patient scenarios, including in-depth medical histories, interview questions, required tests, diagnoses, and medication prescriptions. The app also utilizes the OpenAI GPT3 API to give users feedback and scores evaluating their performance.

I designed and developed a solid software architecture, from database setup to back-end and front-end development and deployment. I carefully selected the best technology stack to ensure optimal performance, scalability, and user experience. Despite the tight timeline, I delivered the MVP on schedule while maintaining excellent communication throughout the project lifecycle with the client.

The final product exceeded the client's expectations, resulting in a delighted customer.

Crafted an eCommerce website called webjacket.com. As part of this project, I utilized HTML5 canvas and Fabric.io, a JavaScript library for drawing complex shapes and graphics on the web, to allow users to customize jackets by selecting sizes, colors, patches, and embroidery. To achieve this, I also implemented a rich yet straightforward Forms Wizard to guide users through customization. For the website's back end, I utilized Node.js along with TypeScript and PostgreSQL for the database. For payments, I integrated purchases with authorize.net, a payment gateway that enables businesses to accept electronic payments online.